alamb commented on code in PR #17796:
URL: https://github.com/apache/datafusion/pull/17796#discussion_r2388103532
##########
datafusion/datasource-csv/src/file_format.rs:
##########
@@ -582,20 +582,25 @@ impl CsvFormat {
}
}
- let schema = build_schema_helper(column_names,
&column_type_possibilities);
+ let schema = build_schema_helper(column_names,
column_type_possibilities);
Ok((schema, total_records_read))
}
}
-fn build_schema_helper(names: Vec<String>, types: &[HashSet<DataType>]) ->
Schema {
+fn build_schema_helper(names: Vec<String>, types: Vec<HashSet<DataType>>) ->
Schema {
let fields = names
.into_iter()
.zip(types)
- .map(|(field_name, data_type_possibilities)| {
+ .map(|(field_name, mut data_type_possibilities)| {
// ripped from
arrow::csv::reader::infer_reader_schema_with_csv_options
// determine data type based on possible types
// if there are incompatible types, use DataType::Utf8
+
+ // ignore nulls, to avoid conflicting datatypes (e.g. [nulls,
int]) being inferred as Utf8.
+ data_type_possibilities.remove(&DataType::Null);
+
match data_type_possibilities.len() {
+ 0 => Field::new(field_name, DataType::Null, true),
Review Comment:
I agree this makes sense. Some context might help too:
```suggestion
// Return Null for columns with only nulls / empty files
// This allows schema merging to work when reading folders
// such files along with normal files.
0 => Field::new(field_name, DataType::Null, true),
```
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